Learn how Budget Board and Maybe differ in their key features, development activity, technology stack and community adoption, so you can decide which of these budgeting apps is best for you.
Last 30 days
Last commit
16 hours agoRepository age
6 yearsVersion
v3.8.2License
AGPL-3.0Repository
teelur/budget-board
Last 30 days
This repository was archived by the owner and is no longer maintained.
Last commit
1 year agoRepository age
3 yearsVersion
v0.6.0License
AGPL-3.0Self-hosted
YesRepository
maybe-finance/maybe
Both Budget Board and Maybe have their unique strengths and serve similar purposes effectively. Consider your specific needs regarding popularity, growth, activity, maturity, licensing and features when making your decision.
Maybe significantly outpaces Budget Board in community adoption with 54,212 stars compared to 890 stars on GitHub. This 60.9x difference suggests Maybe has a much larger and more active community. In terms of developer contributions, Maybe has 5,675 forks, indicating strong developer engagement.
Budget Board is growing faster, adding 6 stars in the last 30 days (+0.7%) against losing 47 stars for Maybe (-0.1%). Budget Board is the smaller project of the two, so it is closing the gap rather than extending a lead.
Budget Board shows more recent development activity with its last commit 16 hours ago, while Maybe was last updated 1 year ago. This suggests Budget Board is being more actively maintained.
Budget Board has been in development longer, starting 6 years ago, compared to Maybe which began 3 years ago. This 3.6-year head start suggests Budget Board may have more mature features and established processes.
Both projects use the AGPL-3.0 license, providing identical terms for usage and distribution.
Both tools serve similar use cases in Budgeting Apps. However, they also have distinct specializations: Maybe extends into Investment Tracking.
Maybe provides self-hosting options for complete data control and customization, while Budget Board may be primarily cloud-based or require different deployment approaches.
vs
vs
vs
vs
vs
vs
vs
vs
vs
vs
vs
vs
vs
vs
vs
vs